Indirect estimation of agent-based models.An application to a simple diffusion model
AbstractStarting from an agent-based interpretation of the well-known Bass innovation diffusion model, we perform a Montecarlo analysis of the performance of a method of simulated moment estimator. We show that nonlinearities of the moments lead to a small bias in the estimates in small populations, and prove that our estimates are consistent and converge to the true values as population size increases. Our approach can be generalized to the estimation of more complex agent-based models. However, a trade-off emerges between model inadequacy and data inadequacy. This is particularly severe when only aggregate information is available, as common with diffusion data.
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Bibliographic InfoPaper provided by LABORatorio R. Revelli, Centre for Employment Studies in its series LABORatorio R. Revelli Working Papers Series with number 118.
Date of creation: 2012
Date of revision:
diffusion model; method of simulated moments; estimation;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
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